FGKA: a Fast Genetic K-means Clustering Algorithm


In this paper, we propose a new clustering algorithm called <i>Fast Genetic K-means Algorithm (FGKA)</i>. FGKA is inspired by the Genetic K-means Algorithm (GKA) proposed by Krishna and Murty in 1999 but features several improvements over GKA. Our experiments indicate that, while K-means algorithm might converge to a local optimum, both FGKA and GKA always converge to the global optimum eventually but FGKA runs much faster than GKA.

DOI: 10.1145/967900.968029

Extracted Key Phrases


Citations per Year

95 Citations

Semantic Scholar estimates that this publication has 95 citations based on the available data.

See our FAQ for additional information.

Cite this paper

@inproceedings{Lu2004FGKAAF, title={FGKA: a Fast Genetic K-means Clustering Algorithm}, author={Yi Lu and Shiyong Lu and Farshad Fotouhi and Youping Deng and Susan J. Brown}, booktitle={SAC}, year={2004} }